The next evolution in malware detection. SYARA combines the power of traditional YARA with semantic AI, enabling you to detect threats that change their words but not their intent.
YARA relies on exact string matches. Attackers simply rephrase their malicious content to evade detection.
GenAI can generate infinite variations of malicious prompts, making static rules obsolete.
Security teams spend countless hours writing rules for every possible variation of an attack.
A multi-layered approach combining traditional pattern matching with AI-powered semantic analysis
Text, Images, Audio, Video
Traditional YARA regex patterns
⚡ Low CostSBERT embeddings for intent matching
💡 Moderate CostFine-tuned models for pattern detection
🎯 Higher CostGPT-4 / Open source models
🚀 Highest CostImage/Audio/Video similarity
🖼️ Moderate CostMatched Rules & Confidence Scores
💡 Smart Optimization: SYARA automatically executes layers in order of cost-efficiency, only invoking expensive models when necessary.
Everything you need to detect evolving threats in the GenAI era
Detect malicious intent even when the exact words change. Uses SBERT and transformer models to understand meaning, not just keywords.
"ignore previous instructions" matches
"disregard prior prompts"
Leverage GPT-4 or open-source LLMs for the most sophisticated threat detection. Perfect for zero-day attacks.
Detect malicious images, audio, and video using perceptual hashing. Identify phishing logos and deepfake content.
Fine-tuned models trained on your specific threat landscape for maximum precision and minimal false positives.
Automatic execution ordering from cheapest (regex) to most expensive (LLM). Only pays for what you need.
Bring your own models, embeddings, and preprocessing pipelines. Integrate with your existing security stack.
Protect your LLM applications from malicious prompts designed to bypass safety guidelines.
Identify phishing websites and emails using both text analysis and logo/image matching.
Detect attempts to jailbreak AI systems using DAN mode and similar techniques.
Hunt for injected scripts and XSS attacks with semantic pattern matching.
Detect malware UI screenshots, icons, and visual artifacts using perceptual hashing.
Identify attempts to extract training data, system prompts, or sensitive information.
Watch how easy it is to detect sophisticated threats
Coming Soon: Complete Tutorial Video
Learn how to write your first SYARA rule and detect prompt injection attacks
pip install syara[all]rule prompt_injection: security
{
strings:
$s1 = "ignore previous" nocase
similarity:
$s2 = "ignore instructions" 0.8
condition:
$s1 or $s2
}import syara
rules = syara.compile('rules.syara')
text = "Please disregard prior instructions"
matches = rules.match(text)
if matches[0].matched:
print("🚨 Threat detected!")SYARA is a non-profit, community-driven project
Join hundreds of security researchers using SYARA to detect next-gen threats